The long term goal for this project is to develop a comprehensive, dynamic model of the disease processes that affect muscle tissue, thereby providing a new and effective tool for discovering and understanding the underlying mechanisms of the many neuromuscular diseases and chronic conditions. This particular proposal represents the continuation of an established, interdisciplinary research effort, involving computer scientists and experts in neuromuscular disease. Our previous work has led to the development of a simple morphometric model of the process(s) of denervation and reinnervation, which is of paramount importance because: (1) the extent and progression of this two-step process is difficult to assess clinically, (2) it is a common factor in a large number of neuromuscular diseases, and (3) we have easy access to a uniquely useful means of quantifying the denervation-reinnervation process by means of a statistically tractable measure of fiber-type grouping, which we developed. Extensive expansion of this model, and its adaptation to chronic myopathies, is the central focus of the current proposal. The hypothesis to be tested is that a computer-driven, dynamic model - quantifying and displaying muscle morphology as a function of the sizes of known but unmeasurable disease factors - can be used to define a set of morphologic measures which can "work backwards" from a real biopsy to quantify the presences and severity of some or all of the disease factors. With the disease factors quantified, it should be possible (1) to draw clearer distinctions between various disease entities, thus aiding in diagnosis, patient management, and in selecting patients for clinical research protocols, (2) devise improved treatments based on a quantitative understanding of which causative factors are present, and (3) to understand better the basic biology behind neuromuscular disease by being able to decipher the complex morphologic picture into its biologically significant component parts.